logi.hist.plot2: Plot logistic regression

Description

Plot combined graphs for logistic regressions

Usage

logi.hist.plot2(independ, depend, logi.mod = 1, type = "dit", 
boxp = TRUE, rug = FALSE, ylabel = "Probability", ylabel2 = "Frequency", 
xlabel = "", mainlabel = "", las.h = 1, counts = FALSE, cex.p = 1, 
pch.dit = 1, incre = 0.02, ...)

Arguments

independ

explanatory variable

depend

dependent variable, typically a logical vector

logi.mod

type of fitting, 1 = logistic; 2 = "gaussian" logistic

type

type of representation, "dit" = dot plot; "hist" = histogram

boxp

TRUE = with box plots, FALSE = without

rug

TRUE = with rug plots, FALSE = without

ylabel

y-axis label

ylabel2

2nd y-axis label

xlabel

x-axix label

mainlabel

overall title for plot

las.h

orientation of axes labels (0 = vertical, 1 = horizontal

counts

add counts above histogram bars

cex.p

size of points in dotplots

pch.dit

Either an integer specifying a symbol or a single character to be used as the default in plotting points. See points for possible values and their interpretation.

incre

increment, i.e., separation between neighbour points in the dotplot.

…

additional options passed to logi.hist

Value

A combined logistic regression plot

References

De la Cruz Rot, M. 2005. Improving the Presentation of Results of Logistic Regression with R. ESA Bulletin 86:41-48.

Examples

Run this code

# NOT RUN {
data(aq.trans, package="popbio")

aq.trans$survived<-aq.trans$fate!="dead"

a<-subset(aq.trans, leaf<50 & stage!="recruit", c(leaf,survived))

logi.hist.plot2(a$leaf,  a$survived, 
type="hist", boxp=FALSE, counts=TRUE, int=10, 
ylabel="Survival probability", ylabel2="Number of plants", 
 xlab="Number of leaves" )

b<-glm(survived ~ leaf, binomial, data=a)
 summary(b)


# }

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